The Inference Report

October 17, 2026

The SWE-rebench rankings hold steady at the top, with Anthropic's Fable 5 maintaining 64.5% and the same seven models occupying positions one through seven as before. Grok 4.5 remains second at 63.8%, Opus 5 third at 63.4%, and the ordering unchanged through Claude CodeAgent at 60.4%. Below that tier, movement exists but stays contained: JunieAgent holds sixth place, Cursor's agent drops slightly in the field but remains measurable, and the full-parameter models like Qwen variants continue their lower placements. The benchmark methodology itself remains sound, it tests actual repository-level software engineering tasks with controlled evaluation conditions and reports confidence intervals that reflect genuine measurement uncertainty rather than false precision. What's notable is the absence of dramatic reshuffling despite the dense model ecosystem now tracked. The top tier separation, where Fable 5 leads by 0.7 percentage points over Grok 4.5 within their respective confidence bands, suggests these models have approached a performance ceiling on this particular task distribution, or that the benchmark is now saturating around what current agentic approaches can solve. The Artificial Analysis leaderboard, by contrast, shows far more churn across 477 entries, with Beam 1.0 entering at position 59 and every model below shifting down one rank, indicating that general instruction-following and reasoning tasks continue to stratify models more clearly than the specific coding challenge domain where the top performers cluster.

Cole Brennan

Daily rankings from SWE-rebench, a benchmark designed to fairly compare LLM capabilities on real-world software engineering tasks. Unlike other evaluations, it uses a standardized scaffolding for all models, continuously updates its dataset to prevent contamination, and runs each model five times to account for stochastic variance.

#ModelScore
1AnthropicFable 5 [high]Model64.5%± 1.41%
2GrokGrok 4.5 [high]Model63.8%± 0.60%
3AnthropicOpus 5 [high]Model63.4%± 1.35%
4Z.aiGLM-5.2 [high]Model62.9%± 1.19%
5OpenAIGPT-5.6 Sol [medium]Model62.3%± 1.83%
6JunieJunieAgent61.8%± 0.54%
7AnthropicClaude CodeAgent60.4%± 1.03%
8OpenAICodexAgent58.0%± 1.29%
9AnthropicSonnet 5 [high]Model56.8%± 0.94%
10CursorCursorAgent51.7%± 0.84%

Artificial Analysis composite index across coding, math, and reasoning benchmarks.

#ModelScoretok/s$/1M
1Claude Opus 5.557.698$8.00
2Claude Sonnet 5.556144$4.00
3Muse Wonder Full55.80$0.00
4Claude Fable 5.153.469$20.00
5GPT-6 Astra52.761$20.00
6Gemini 4 Argon52.60$4.00
7Muse Wonder52.4184$8.00
8GPT-6.1 Sol51.860$4.00
9Claude Opus 550.80$10.00
10Claude Fable 549.60$20.00

Output tokens per second — higher is faster. Minimum intelligence score of 40.

#Modeltok/s
1Claude Haiku 5.5243
2Ling 3.1 Flash219
3Muse Wonder184
4Gemini 3.8 Flash145
5Claude Sonnet 5.5144
6Muse Spark 1.3130
7GPT-5.6 Terra128
8Claude Opus 5.598
9Step 5 Preview91
10Grok 4.784

Blended cost per 1M tokens (3:1 input/output) — lower is cheaper. Minimum intelligence score of 40.

#Model$/1M
1Claude Haiku 5.5$0.20
2GLM-5.3-Flash$0.237
3Ling 3.1 Flash$0.45
4MiMo-V2.6-Pro$0.544
5Step 5 Preview$1.43
6Gemini 3.8 Flash$1.50
7Muse Spark 1.3$2.00
8GLM-5.3$2.15
9Grok 4.7$3.00
10Qwen3.8 Max$3.00